Our group includes PostDocs, PhD students, and student assistants, and is headed by Prof. Dr. Hasso Plattner. If you are interested in our work or want to join our team, please contact Dr. Matthias Uflacker.

Our team is giving a series of lectures and seminars with a focus on enterprise systems design and in-memory data management. Strong links to the industry ensure a close connection between theory and its implementation in the real world.

Our research focuses on the principles of in-memory data management on modern hardware and the integration of different hard- and software systems to meet business requirements. This involves studying the conceptual and technological aspects of modern enterprise applications as well as tools and methods for enterprise systems design.

We continually strive to translate our research into practical outputs that improve the quality of enterprise applications. A close link to industry partners ensures relevance and impact of our work. Get here an overview of our current and previous projects.

Recognizing Compound Events in Spatio-Temporal Soccer Data

In the world of professional soccer, performance analytics about the skill level of a player and the overall tactics of a match are supportive for the success of a team. These analytics are based on positional data on the one hand and events about the game (e.g. pass, shot on target) on the other hand. The positional data of the ball and players is tracked automatically by cameras or via sensors. However, the events are still captured manually by human, which is time-consuming and error-prone.

In this research project, we introduce a novel approach to detect events in soccer matches by utilizing different machine learning. As input for the machine learning techniques (e.g. neural networks, random forest, support vector machines, k-nearest neighbor, we used several time-dependent features, which were calculated on the basis of the positional data. The evaluation of the results showed that it is possible to recognize soccer events in spatio-temporal data with a high accuracy. Apart of that, we discovered that the size of the used model and the data granularity have a strong influence on the quality of the predicted results.

Open Positions

We are proud to announce " A Course in In-Memory Data Management" by Prof. Dr. h.c. Hasso Plattner. This book is the culmination of six years work of in-memory research. As such, it provides the technical foundation for combined transactional and analytical workloads inside one single database as well as examples of new applications that are now possible given the availability of the new technology. The book is available at Springer.